Characterization of a double emulsion system (oil‐in‐water‐in‐oil emulsion) with low solid fats: Microstructure
Bibliographic record
Abstract
Abstract A double emulsion system [oil‐in‐water‐in‐oil (O/W/O)] with 16.3% (w/w) water and 83% (w/w) oil was prepared and stabilized using a novel method of mixing two oil‐in‐water (O/W) emulsions together. The first emulsion consisted of 85% (w/w) liquid canola oil, 14.4%(w/w) water, 0.5% (w/w) sodium caseinate, and 0.1% (w/w) lecithin and the second emulsion contained 73% (w/w) canola oil, 8% (w/w) palm‐cotton stearin (50∶50), 0.2% (w/w) lecithin, 18.2% (w/w) water, and 0.6% (w/w) sodium caseinate. Mixing the two emulsions (50∶50) by weight produced a product with 79% (w/w) liquid canola oil and 4% (w/w) palm‐cotton stearin. The two O/W emulsions were prepared separately at 50°C, mixed together at 45°C for 2–5 min, and then supercooled in a −5°C ice/salt bath while mixing at low shear rates (2,000–3,000 rpm). Under supercooling conditions the fat globules in the second emulsion (containing liquid oil and stearin) began to break down as a result of fat crystal growth and shearing action and release plastic fat. During this stage, the continuous aqueous phase underwent a phase transition and the emulsion viscosity dropped from 37,000–50,000 to 250 cP. The released plastic fat continued to harden as the temperature dropped and stabilized the first O/W emulsion (containing only liquid oil). The low shear rate mixing was stopped when the temperature dropped below 15°C and before the O/W/O emulsion hardens. Microstructural analysis of the first emulsion before and after supercooling showed essentially intact fat globules. The microstructure of the second emulsion before supercooling showed the same intact globules as the first emulsion, but after supercooling, an amorphous mass with only a few intact globules was seen. By mixing the two emulsions together and supercooling, a stable O/W/O emulsion was formed with plastic fat as the continuous phase and the first O/W emulsion as the dispersed phase.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".